# Using dplyr, I add each missing row into a new df:
missing <- data.frame(cutdist=c(20000, 20000, # AlbCen
20000, 20000,# Assel
20000, 20000, # LOI
18000, 20000, # lome
20000, 20000, # messi
20000, 20000, # pliens
18000, 18000, 20000, 20000, 20000, # PT
20000, 20000, #SanCamp
18000, 20000, #Serra
20000), #TJ
avg= c(NA, NA,
NA, NA,
NA, NA,
NA, NA,
NA, NA,
NA, NA,
NA, NA, NA, NA, NA,
NA, NA,
NA, NA,
NA),
sdev= c(NA, NA,
NA, NA,
NA, NA,
NA, NA,
NA, NA,
NA, NA,
NA, NA, NA, NA, NA,
NA, NA,
NA, NA,
NA),
n= c(NA, NA,
NA, NA,
NA, NA,
NA, NA,
NA, NA,
NA, NA,
NA, NA, NA, NA, NA,
NA, NA,
NA, NA,
NA),
se= c(NA, NA,
NA, NA,
NA, NA,
NA, NA,
NA, NA,
NA, NA,
NA, NA, NA, NA, NA,
NA, NA,
NA, NA,
NA),
first= c(NA, NA,
NA, NA,
NA, NA,
NA, NA,
NA, NA,
NA, NA,
NA, NA, NA, NA, NA,
NA, NA,
NA, NA,
NA),
second= c(NA, NA, NA,
NA,
NA, NA,
NA, NA,
NA, NA,
NA, NA,
NA, NA, NA, NA, NA,
NA, NA,
NA, NA,
NA),
label= c('Before', 'After',
'Before', 'After',
'Before', 'After',
'After-2', 'After-2',
'Before','After',
'Before','After',
'After', 'After-2', 'Before', "After", "After-2",
'Before','After',
'Before', 'After',
'After'),
ci= c(NA, NA,
NA, NA,
NA, NA,
NA, NA,
NA, NA,
NA, NA,
NA, NA, NA, NA, NA,
NA,NA,
NA, NA,
NA),
ID = c('AlbCen', 'AlbCen',
'Assel', 'Assel',
'LOI', 'LOI',
'lome', 'lome',
'Messi','Messi',
'Pliens', 'Pliens',
'PT', 'PT', 'PT', 'PT', 'PT',
'SanCamp','SanCamp',
'Serra', 'Serra',
'TJ'),
Jaccard_change= c(NA, NA,
NA, NA,
NA, NA,
NA, NA,
NA, NA,
NA, NA,
NA, NA, NA, NA, NA,
NA,NA,
NA, NA,
NA))
# Add these missing rows to the all_Jacc df
all_Jacc <- rbind(all_Jacc, missing)
# Rearrange all_Jacc by ID and cutDist and label
all_Jacc <- all_Jacc |>
arrange(ID, cutdist, label)